معرفی
Elise Grosjean is an Assistant Professor in Applied Mathematics at ENSTA Paris. Her research focuses on fluid mechanics, partial differential equation analysis, numerical schemes, reduced order methods, inverse problems, and optimal transport.
- Education: PhD in Applied Mathematics (2022, Sorbonne Université), Master in Mathematics of Modeling (2018, UPMC), Engineer School in Applied Mathematics and Computer Science (2018, Polytech-Paris UPMC), Bachelor in Fundamental Mathematics (2015, UPMC)
Her research integrates finite element/volume methods, programming languages, and numerical simulation of parameterized models from physics and biology. She actively develops reduced basis methods and applies them to tissue regeneration and fluid dynamics problems.
Recent publications highlight her work on meniscus tissue regeneration modeling (2024), error estimates in two-grid reduced basis methods (2024), and numerical simulations using FreeFem++ for 3D bioreactor models and back-and-forth nudging algorithms for wave equations (2023-2024). These works span biomedical engineering, computational mathematics, and inverse problem solving.
She has taught courses on differential-algebraic equations at TU Kaiserslautern and contributed to teaching at ENSTA Paris, Sorbonne Université, and ENSAE. Her technical expertise includes Python, C++, FreeFem++, and model order reduction frameworks.
Elise is affiliated with INRIA-Saclay (current postdoc), RPTU Kaiserslautern (2022-2023), and the Jacques-Louis Lions Laboratory (2018-2022). She also explores intersections between mathematics and art in her creative practice.
